ScopeMaster – Release History
Release 1.5.3 (planned)
- Greater flexibility to identify legitimate users and objects.
Release 1.5.2 22 June 2019
- Slice and dice your user stories like never before (by user, by object, by label). New presentation that will help you improve your user stories faster than ever.
Release 1.5.1 15 June 2019
- Upload a CSV file and map your fields dynamically – importing goes from minutes to seconds.
- Related stories – ideal for regression test targeting, a powerful cross correlation of user stories that touch the same object or user; .
- Export now includes CFP values
- Overhaul of the Labelling UX, it’s now easier than ever to label and organise your requirements, for more efficient working.
- Dozens of usability improvements – because it should be intuitive and easy to do good requirements work.
Release 1.4.5 24 May 2019
- User story title is no longer analysed for data movement intent
- Other usability, cosmetic and stability improvements
Release 1.4.4 6 May 2019
- Interface and ease of use improvements
- Improved IFPUG accuracy
Release 1.4.2 17 April 2019
- NEW Sample Set of User Stories
- Learn from a useful set of annotated examples
- NEW Project Glossary
- Positive quality decisions regarding users and objects of your application
- Interface improvements
- Improved stability, minor bug fixes
- Improved analysis, all objects and users now singularised.
- Jira Plugin – renamed to Story Validator – and now fully GDPR compliant
Release 1.4 29 March 2019
- NEW Productivity Benchmarking
- Establish your team(s)’ benchmarks for productivity.
- Compare your work with industry averages.
- Use the productivity benchmark for new project estimation. Quick calculator included.
- Improved usability – Improve your user stories even faster.
- Improved usability for adding many and re-analysing all user stories
- Improved adherence to COSMIC methodology reporting standards
Release 1.35 6 March 2019
- Delete an entire application in one step
- Improved stability of importing and resizing stories
- Foundations for new features
Release 1.34 11 February 2019
- Improved: minor UI fixes
- Foundations for new features
Release 1.33 15 January 2019
- New: Labels – add user defined coloured labels to your requirements and easily filter by label.
- Improved: add missing stories with as little as two clicks
- Improved: access recommended verbs in editing context.
- Deprecated: readability score.
- Minor fixes.
Release 1.32 7 December 2018
- New: Suggested test cases tab for each user story, positive and negative functional test cases
- New: Suggested test cases report, positive and negative functional test cases
- Improved: stability and performance
Release 1.31 11 November 2018
- New: ScopeMaster Plugin for Jira Cloud Visit the plugin on the Atlasssian Marketplace
- Improved: additional story improvement suggestions.
- New: Introducing the ScopeMaster Quality Score
- Improved: Portfolio level view of quality
Release 1.21 11 October 2018
- Fixed: Adding a multi-line story via the simple add box.
- Fixed: Removed “so that” warning, potentially misleading.
- Fixed: Default user timezone now set.
- Performance improvements
Release 1.2 August 2018
- Improved navigation for faster and easier story correction
- Quickly revert to any previous version of a user story
- Minor UI improvements and browser compatibility fixes
- Performance and security improvements
- Deprecated the text analysis table
- Improved accuracy of defect reporting, by removing list as an expected function.
Release 1.11 (current), 18 July 2018
- NEW Explorer. This is an additional capability that enables portfolio analysis of users and objects.
- As ScopeMaster analyses requirements it builds up an inventory of the users and objects that are maintained across the software systems of your enterprise. These are now visible with an easy-to-navigate explorer, so you can see an enterprise-wide view of the applications in which a particular user or object is maintained.
- Ideal for:
- Planning and estimating the impact of legislative change on corporate systems.
- Insight into potential technical debt across systems.
- Insight relating to application lifecycle planning.
- Identifying risk areas associated with data security
- Minor UI improvements (easier navigation for grooming user stories)
- Improvements to search results.
Release 1.1, 28 June 2018
- Context specific guidance on improving each story. (learn to improve your stories faster)
- Improved meta information about a set of requirements, including changes over time and size statistics.
Production release 1.01, 1 June 2018
- New simple structured user story input (makes it easier to get it right first time!)
- Jira Integration (import stories directly from your Jira repository)
Production release 1.0, 13 May 2018
- Minor bug fixes
- Improved reports and navigation
Pre-Production release 0.91 4 May 2018
- Easier to find and fix consistency errors – improved users and objects display
- Improved help pages
- Improved access to previous versions
- Corrected interpretation of the word “status”
Pre-Production release 0.89 29 March 2018
- New ambiguities reporting (thanks to Richard Bender)
- minor bug fixes
Pre-Production release 0.88, 25 March 2018
- Improved full screen display and responsive menus
- Improved defects report
- Easy navigation back to recently visited user stories
Pre-Production release 0.87, 17 March 2018
- NEW Sortable, searchable table, ideal for story grooming
- Improved text analysis accuracy
- Simplified defects report
- Improved performance for very large projects
Pre-Production release 0.85, 6 March 2018
- NEW Users can share work with others in their organization.
- NEW Share work at the application level: owners can assign read or edit access to others in their organisation.
- NEW Requirement text within square brackets will be ignored from sizing analysis.
- NEW Requirement export/download as csv.
- Improved IFPUG Function Point estimates, with function-by-function details report.
- Improved text analysis accuracy.
- Improved UI and bug fixes.
- Improved searching
- Improved application performance.
- Improvements to application data security.
- Major improvements to server(s) security.
Beta, 14 December 2017
- analyses the text to describe software requirements
- Interprets user story terminology and common active phrases
- identifies candidate users and objects from the entire body of requirements text
- detects potentially defective requirements – ambiguous
- detects potentially defective requirements – omissions
- detects potentially defective requirements – duplicates
- Identifies functional data movements
- Identifies data to be maintained
- estimates the functional size of the software – in Cosmic Function Points
- provides estimates for: cost to develop, defect potentials, resource requirements and likely schedules.
- Accuracy of functional sizing is currently around 70-80% (Nb. manual accuracy can vary by up to 10%)
- Import by text list or csv
- Ability to take a snapshot track the size progression.
- Portfolio view
- Import 2 column spreadsheet
- Basic text analysis engine
- Initial CFP structure